CARD11 signaling determines whether antigen stimulation induces B cells to proliferate or die.

Background: To date, there are limited Australian data on characteristics of people diagnosed with COVID-19 and on how these characteristics relate to outcomes. The ATHENA COVID-19 Study was established to describe health outcomes and investigate predictors of outcomes for all people diagnosed with COVID-19 in Queensland by linking COVID-19 notification, hospital, general practice and death registry data. This paper reports on the establishment and first findings for the ATHENA COVID-19 Study. Methods: Part 1 of the ATHENA COVID-19 Study used Notifiable Conditions System data from 1 January 2020 to 31 December 2020, linked to: Emergency Department Collection data for the same period; Queensland Health Admitted Patient Data Collections (from 1 January 2010 to 30 January 2021); and Deaths Registrations data (from 1 January 2020 to 17 January 2021). Results: To 31 December 2020, a total of 1,254 people had been diagnosed with SARS-CoV-2 infection in Queensland: half were female (49.8%); two-thirds (67.7%) were aged 20–59 years; and there was an over-representation of people living in less-disadvantaged areas. More than half of people diagnosed (57.6%) presented to an ED; 21.2% were admitted to hospital as an inpatient (median length of stay 11 days); 1.4% were admitted to an intensive care unit (82.4% of these required ventilation); and there were six deaths. Analysis of factors associated with these outcomes was limited due to small case numbers: people living in less-disadvantaged areas had a lower risk of being admitted to hospital (test for trend, p < 0.001), while those living in more remote areas were less likely than people living in major cities to present to an ED (test for trend: p=0.007), which may reflect differential health care access rather than health outcomes per se. Increasing age (test for trend, p < 0.001) and being a current/recent smoker (age-sex-adjusted relative risk: 1.61; 95% confidence interval: 1.00, 2.61) were associated with a higher risk of being admitted to hospital. Conclusion: Despite uncertainty in our estimates due to small numbers, our findings are consistent with what is known about COVID-19. Our findings reinforce the value of linking multiple data sources to enhance reporting of outcomes for people diagnosed with COVID-19 and provide a platform for longer term follow-up.

Background Socioeconomic inequalities in mortality are evident in all high-income countries, and ongoing monitoring is recommended using linked census-mortality data. Using such data, we provide the first estimates of education-related inequalities in cause-specific mortality in Australia, suitable for international comparisons. Methods We used Australian Census (2016) linked to 13 months of Death Registrations (2016–17). We estimated relative rates (RR) and rate differences (RD, per 100 000 person-years), comparing rates in low (no qualifications) and intermediate (secondary school) with high (tertiary) education for individual causes of death (among those aged 25–84 years) and grouped according to preventability (25–74 years), separately by sex and age group, adjusting for age, using negative binomial regression. Results Among 13.9 M people contributing 14 452 732 person-years, 84 743 deaths occurred. All-cause mortality rates among men and women aged 25–84 years with low education were 2.76 [95% confidence interval (CI): 2.61–2.91] and 2.13 (2.01–2.26) times the rates of those with high education, respectively. We observed inequalities in most causes of death in each age-sex group. Among men aged 25–44 years, relative and absolute inequalities were largest for injuries, e.g. transport accidents [RR = 10.1 (5.4–18.7), RD = 21.2 (14.5–27.9)]). Among those aged 45–64 years, inequalities were greatest for chronic diseases, e.g. lung cancer [men RR = 6.6 (4.9–8.9), RD = 57.7 (49.7–65.8)] and ischaemic heart disease [women RR = 5.8 (3.7–9.1), RD = 20.2 (15.8–24.6)], with similar patterns for people aged 65–84 years. When grouped according to preventability, inequalities were large for causes amenable to behaviour change and medical intervention for all ages and causes amenable to injury prevention among young men. Conclusions Australian education-related inequalities in mortality are substantial, generally higher than international estimates, and related to preventability. Findings highlight opportunities to reduce them and the potential to improve the health of the population.

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